ﻻ يوجد ملخص باللغة العربية
Blackwells theorem shows the equivalence of two preorders on the set of information channels. Here, we restate, and slightly generalize, his result in terms of random variables. Furthermore, we prove that the corresponding partial order is not a lattice; that is, least upper bounds and greatest lower bounds do not exist.
Suppose we have a pair of information channels, $kappa_{1},kappa_{2}$, with a common input. The Blackwell order is a partial order over channels that compares $kappa_{1}$ and $kappa_{2}$ by the maximal expected utility an agent can obtain when decisi
This paper applies machine learning to optimize the transmission policy of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) networks, where time-division multiple access (TDMA) is used to serve multiple primary users and an energy-co
This paper presents results pertaining to sequential methods for support recovery of sparse signals in noise. Specifically, we show that any sequential measurement procedure fails provided the average number of measurements per dimension grows slower
Consider a channel ${bf Y}={bf X}+ {bf N}$ where ${bf X}$ is an $n$-dimensional random vector, and ${bf N}$ is a Gaussian vector with a covariance matrix ${bf mathsf{K}}_{bf N}$. The object under consideration in this paper is the conditional mean of
In this work a method for statistical analysis of time series is proposed, which is used to obtain solutions to some classical problems of mathematical statistics under the only assumption that the process generating the data is stationary ergodic. N